Enhancing inclusivity in clinical trials: Model-informed drug development for pregnant individuals in the era of personalized medicine

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY CPT: Pharmacometrics & Systems Pharmacology Pub Date : 2024-08-18 DOI:10.1002/psp4.13218
André Dallmann, Peter L. Bonate, Janelle Burnham, Blessy George, Lynne Yao, Jane Knöchel
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Factors that may contribute to this gap include hesitancy of healthcare providers and patients, complex trial designs, ethical concerns, and the potential risk to the pregnant individual and fetus.<span><sup>1</sup></span> Consequently, pregnant and lactating individuals are prescribed potentially beneficial medicines with limited safety and efficacy information or guidance on optimal dosing for this patient population. Thus, it is vital to include pregnant individuals in the drug development process and engage early with global regulatory agencies.</p><p>Model-informed drug development (MIDD) methods are a selection of various quantitative methods that help to balance the risks and benefits of drug products in development. As such, these techniques are paramount to maximize the number of safe and effective medicines for pregnant individuals. 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For example, if an individual becomes pregnant while on an investigational agent, they may consent to the collection of pharmacokinetic data that can be used to identify any changes in dosing that may be needed during pregnancy. However, at the time of marketing approval, there is generally little to no human data to inform the safety of drugs and biological products when used during pregnancy. Consequently, the FDA has the authority to issue postmarketing required (PMR) studies to collect information on the safety of medicines used during pregnancy. PMR studies are considered during the review of a marketing application and may be issued for treatments that will be used in females of reproductive potential when there is a need for data to inform on the safety of the use of the treatment during pregnancy.<span><sup>8</sup></span> In a recent review, only 16% of drugs that may be used in females of reproductive potential were issued PMRs for pregnancy (and/or lactation) studies.<span><sup>9</sup></span> However, there has been increasing stakeholder interest in the importance of collecting data in pregnant individuals as illustrated by the recommendations of the Task Force on Research Specific to Pregnant Women and Lactating Women (PRGLAC). 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Abstract

For decades, the administration of medication to pregnant and lactating individuals has occurred and the majority of pregnant individuals commonly receive medication during pregnancy. However, the inclusion of pregnant individuals is limited or is significantly underrepresented in global clinical trial research. Factors that may contribute to this gap include hesitancy of healthcare providers and patients, complex trial designs, ethical concerns, and the potential risk to the pregnant individual and fetus.1 Consequently, pregnant and lactating individuals are prescribed potentially beneficial medicines with limited safety and efficacy information or guidance on optimal dosing for this patient population. Thus, it is vital to include pregnant individuals in the drug development process and engage early with global regulatory agencies.

Model-informed drug development (MIDD) methods are a selection of various quantitative methods that help to balance the risks and benefits of drug products in development. As such, these techniques are paramount to maximize the number of safe and effective medicines for pregnant individuals. Here, we discuss a roadmap of how each MIDD method (Figure 1) can be used to address the various challenges faced in this vulnerable patient population.

As stated earlier, pregnant individuals have historically been excluded from clinical therapeutics development trials and continue to be underrepresented in research. Importantly, failure to establish the correct dose/dosing regimen and the safety of treatments used during pregnancy may compromise the health of pregnant individuals and their fetuses. Under certain circumstances, it is ethically justifiable to include pregnant individuals in clinical trials in both the premarketing and postmarketing setting.7 Additionally, it may also be ethically justifiable to obtain information on individuals who become pregnant while enrolled in a clinical trial. For example, if an individual becomes pregnant while on an investigational agent, they may consent to the collection of pharmacokinetic data that can be used to identify any changes in dosing that may be needed during pregnancy. However, at the time of marketing approval, there is generally little to no human data to inform the safety of drugs and biological products when used during pregnancy. Consequently, the FDA has the authority to issue postmarketing required (PMR) studies to collect information on the safety of medicines used during pregnancy. PMR studies are considered during the review of a marketing application and may be issued for treatments that will be used in females of reproductive potential when there is a need for data to inform on the safety of the use of the treatment during pregnancy.8 In a recent review, only 16% of drugs that may be used in females of reproductive potential were issued PMRs for pregnancy (and/or lactation) studies.9 However, there has been increasing stakeholder interest in the importance of collecting data in pregnant individuals as illustrated by the recommendations of the Task Force on Research Specific to Pregnant Women and Lactating Women (PRGLAC). The PRGLAC report included 15 recommendations to increase the availability of safe and effective therapies specific to pregnant and lactating individuals.10

Although diversity and inclusion in clinical trials and personalized medicine are current paradigms, there is a lack of information about drug safety and efficacy in pregnant individuals. Various stakeholder efforts, further outlined in Table 1, strive to bridge this gap. While incentives for conducting clinical trials in pregnant individuals remain limited, regulatory agencies are increasingly emphasizing the need for PMR studies to gather essential information. To advance drug development in this population, it is crucial to engage early with regulatory agencies and explore MIDD tools which present promising avenues to broaden the access of pregnant individuals to the benefits of clinical research.

No funding was received for this work.

J.K. is an employee of AstraZeneca and owns stock. All other authors declared no competing interests for this work.

The views expressed in this perspective are the authors' views alone. They do not reflect the official views or guidance from the US Food and Drug Administration, nor should they be construed as such.

As Editor-in-Training of CPT: Pharmacometrics & Systems Pharmacology Jane Knöchel was not involved in the review or decision process for this paper.

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增强临床试验的包容性:在个性化医疗时代,针对孕妇的模型化药物开发。
几十年来,对孕妇和哺乳期妇女用药的情况时有发生,大多数孕妇通常在怀孕期间接受药物治疗。然而,在全球临床试验研究中,将孕妇纳入研究范围的情况非常有限,或者说代表性严重不足。造成这一差距的因素包括医疗服务提供者和患者的犹豫不决、复杂的试验设计、伦理问题以及对孕妇和胎儿的潜在风险1 。因此,将孕妇纳入药物开发过程并尽早与全球监管机构接触至关重要。"以模型为依据的药物开发(MIDD)方法是对各种定量方法的精选,有助于平衡开发中药物产品的风险和收益。因此,这些技术对于最大限度地为孕妇提供安全有效的药物至关重要。在此,我们将讨论如何利用每种 MIDD 方法(图 1)来应对这一弱势患者群体所面临的各种挑战的路线图。如前所述,孕妇历来被排除在临床治疗药物开发试验之外,而且在研究中的代表性仍然不足。重要的是,如果不能确定正确的剂量/给药方案以及孕期治疗的安全性,可能会危及孕妇及其胎儿的健康。在某些情况下,将孕妇纳入上市前和上市后的临床试验在伦理上是合理的。7 此外,获取在临床试验期间怀孕的患者的信息在伦理上也是合理的。例如,如果一个人在服用研究药物期间怀孕了,他们可以同意收集药代动力学数 据,这些数据可用于确定怀孕期间可能需要改变的用药剂量。然而,在批准上市时,通常很少或根本没有人类数据来说明妊娠期使用药物和生物制品的安全性。因此,美国食品和药物管理局有权发布上市后要求(PMR)研究,以收集有关孕期用药安全性的信息。PMR 研究是在审查上市申请时考虑的,当需要数据来说明妊娠期使用治疗的安全性时,可对具有生殖潜能的女性使用的治疗进行PMR 研究。9 然而,正如孕妇和哺乳期妇女研究特别工作组(PRGLAC)的建议所表明的那样,利益相关者越来越关注收集孕妇数据的重要性。PRGLAC 报告包括 15 项建议,旨在增加针对孕妇和哺乳期妇女的安全有效疗法的可用性。10 虽然临床试验和个性化医疗的多样性和包容性是当前的典范,但有关孕妇用药安全和疗效的信息仍然匮乏。表 1 进一步概述了各利益相关方为弥补这一差距所做的努力。虽然在孕妇中开展临床试验的激励措施仍然有限,但监管机构越来越强调开展 PMR 研究以收集重要信息的必要性。为了推动这一人群的药物开发,尽早与监管机构接触并探索 MIDD 工具至关重要,这些工具为扩大孕妇获得临床研究的益处提供了大有可为的途径。所有其他作者声明与本研究无利益冲突。本文观点仅代表作者个人观点,不反映美国食品和药物管理局的官方观点或指导,也不应被理解为美国食品和药物管理局的观点或指导:作为《CPT:Pharmacometrics & Systems Pharmacology》的培训编辑,Jane Knöchel 没有参与本文的审稿或决策过程。
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11.40%
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146
审稿时长
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